Social Media: Artificial Intelligence and the Holy Grail
In 2016 Internet advertising has overtaken all traditional media including TV (Figure 1). While over 40% of the money is spent on the search ads, social media is catching up with more than 24% of total spending. Social media as a channel provides unique opportunities for marketers including micro-targeting and two-way user engagement. But the biggest challenge with social media is the amount of data and interactions generated — only on twitter users generate over 400,000 tweets every single minute. With this amount of data Artificial Intelligence becomes paramount to efficiently engage consumers at scale.
Still, finding the Holy Grail of social media with the help of Artificial Intelligence wont be an untroublesome adventure. The recent Cambridge Analytica scandal[1] is very likely to result in much more strict data governance policies which will limit companies’ ability to use AI for micro-targeted social media campaigns. But beside hyper-personalization there are more than enough use-cases for AI to shine.
Social Media Listening
Social media listening has been done for some time with great success thanks to advancements in machine learning and Natural Language Processing (NLP). It helps marketers to get valuable data to enable social marketing and care:
- Brand Intelligence. With the ability to track and interpret user interactions on social media marketers can gain valuable insights on brand performance. Companies like TalkWalker track brand awareness, what users think about brands, products, messages and who these users are (gender, location etc.).
- Competitive Intelligence. The same tools that are used for understanding brand performance can provide vital intelligence on the competition. Cortex tracks each competitor update, analyzes its content and performance, and optimizes posts to increase engagement. This allows marketers to adjust their strategy and respond timely to competition actions.
- Social Care. With conversations on social media being rather short, efficient customer care requires quick transition of the customers to the right care channel which will be able to resolve the issue. For example, Conversational leverages analytics to identify customers having specific problems and automatically connect them with the right care agent.
Content Publishing/ Engagement
With the amount of engagement on social media surging, content development efforts are growing as well. Content creation and management is an area where more AI involvement is expected to be seen in the near future:
- Content Selection. Considering the amount of content and interactions data available (likes, shares), AI can be used to select content which will resonate with the customers the most. NY Times has developed an application to select the best stories to publish each day from the hundreds of stories they have in the pipeline.
- Content Curation. Content curation is process of sorting through large amounts of content on the web and presenting the most relevant content in a meaningful and organized way. Bytedance is one of the companies that leverages AI for content curation based on user profile and context. This allows users to have personalized content selection rather than generic set of posts, videos etc.
- Content Generation. Most likely we wont see AI being able to generate creative content in the near future, but business content creation and content tuning for the needs of specific audiences is something that is already done today. Narrative Science provides capabilities to adapt content for different audiences, for example the same story may be changed to target existing customers, non-customer, or competitive customers.
After all, maybe the days when AI’s will have their own Facebook pages are not that far away.
